Research Data

Dyslipidemia is a common risk factor for cardiovascular disease although the relationship between circulating lipids and abdominal aortic aneurysm (AAA) is unclear. We conducted a lipidomic analysis with the objective of identifying serum lipid species associated with AAA presence. Secondary analyses assessed the ability of models incorporating lipidomic features to improve stratification of AAA patients from controls with peripheral artery disease (PAD) beyond traditional risk factors.

Liquid-chromatography tandem mass spectrometry (LC-MS/MS) was used to profile serum lipids from patients with AAA (n=91) or PAD (n=103). Adjusted binary logistic regression was used to identify lipids associated with AAA. Classification models were created based on a combination of 1) traditional cardiovascular risk factors only, or 2) lipidomic features and traditional risk factors. Receiver operator characteristic (ROC) curves were generated to assess the performance of the models. Of 314 identified lipids, 4 diacylglycerol and 10 triacylglycerol lipid species were associated with AAA after adjusting for other risk factors and correcting for multiple comparisons. Stratification of AAA patients from PAD controls was significantly improved when combining lipidomic features with clinical characteristics (mean area under ROC curve: 0.775; 95% CI: 0.770 – 0.780) compared to clinical features alone (mean area under ROC curve: 0.735; 95% CI: 0.729 - 0.741). Conclusion: We identified a group of linoleic acid-containing triacylglycerols and diacylglycerols to be significantly associated with AAA presence. Inclusion of these lipids in a multivariate analysis significantly improved prediction of the presence of AAA compared to traditional risk factors alone.

Data is in an excel spreadsheet.